| Summary: | Currently, it is standard to use tracked handheld controllers for interaction in immersive virtual reality (VR). However, since VR interactions are becoming more natural with hand tracking, it is important to provide hands-free alternatives for selection and system control tasks. As such, this study aims to provide an exploratory evaluation of the effectiveness and efficiency of commonly used hands-free interfaces in selection and system control tasks. Nine interaction methods were evaluated while performing a Fitts’ law task with nine advanced users of VR in a within-subject experiment. We evaluated handheld controllers as a baseline, against head gaze, eye gaze, and voice commands for pointing at the targets, and dwell time and voice commands to confirm selections. We found that using eye gaze with a <inline-formula> <tex-math notation="LaTeX">$\mathrm {500 ms}$ </tex-math></inline-formula> dwell time proved to be the hand-free method with the highest performance, matching the handheld controllers and being preferred by users. The evaluation also showed that using a multimodal approach to selection, especially using the voice, decreases performance, but increases effectiveness. Moreover, we verified that Fitts’ law can be applied to hands-free methods, but its usage is limited when the methods have very short travel times. We then suggest selections per minute as a more robust comparative performance metric. Further studies should expand the audience and interaction tasks and focus on the confirmatory method of selection.
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